Adaptive Gain Research Articles

Retargeting control of a multi-tethered satellite formation at sun-earth libration point

This paper investigates the nonlinear dynamics and control for three-dimensional retargeting maneuver of a flexible multi-tethered satellite formation at the sun-earth L2 libration point. In Hill’s problem, a fundamental modeling strategy is adopted to develop two dynamic models, a flexible one for dynamic simulation and a rigid one for control design. Both the flexibility of tethers and the attitude motions of satellites have been incorporated into the system dynamics. Not limited to the system under consideration, this flexible model could be generally exploited to describe multi-tethered satellite formation systems with arbitrary configurations. Besides, a nonlinear model-predictive control law for the retargeting problem of concern is developed to achieve the desired attitude of the system. The attitude control of the satellites is performed during retargeting process based on optimal control using a switching on–off method. For the ease of tracking an optimal trajectory of tether libration states and control input, an adaptive gain control law is proposed to retarget the flexible system. Finally, numerical case studies have been carried out to evaluate the dynamic behaviors of the system and to demonstrate the effectiveness of the proposed retargeting controller.

Stable Simultaneous Inertia and Disturbance Torque Identification for SPMSM Drive Systems Subject to Mismatched Rotor Flux Linkage

In surface-mounted permanent magnet synchronous motor (SPMSM) drives, the distinguished orthogonal-principle-based method is presently popular for handling simultaneous inertia and disturbance torque estimation due to its simplicity and ease of implementation. Nevertheless, it is facing challenges posed by the rotor flux-linkage mismatch, zero-derivative constraint, and operating-condition limitation. To cope with these issues, this article presents an alternative scheme, which explores a stable simultaneous inertia and disturbance torque estimation with the real-time flux-linkage correction. First, an Adaline-based estimator is developed to acquire the disturbance torque. With an input-adaptive learning rate designed by the Lyapunov theory, this estimator can prevent potential convergence failure. Then, an extended sliding-mode observer for inertia estimation is proposed regarding the inertia as a new system state. By using the identified disturbance torque to devise an adaptive feedback gain, this observer guarantees the asymptotic error convergence. Finally, to counteract the flux-linkage mismatch, a flux-linkage observer with a time-varying learning rate is constructed utilizing the Adaline technique. Moreover, it attains robust convergence and only has one to-be-adjusted parameter. The effectiveness of our scheme is validated by abundant simulations and real-time experiments.

Prescribed Performance-Based Powered Descent Guidance for Step-Shaped Hazardous Terrains

The planetary powered descent guidance problem for step-shaped hazardous terrains is investigated in this article based on prescribed performance function (PPF) methodology. Initially, the distances between the lander and step-shaped terrains around the landing site have been formulated in a new form boundaryfunction using PPF, in which a new step-shaped boundary PPF is specifically designed to constrain the lateral motion. Furthermore, a fixed-time convergent PPF is chosen to coordinate the vertical motion. Next, to avoid the collision with step-shaped terrains and planetary surface, a feedback guidance algorithm is proposed based on the backstepping method. Considering a large guidance gain is beneficial for the lander to move away from the boundary PPF, but excessive control acceleration will be generated when the landing error is large. To solve this problem, an adaptive guidance gain is designed using Gaussian function. Finally, the feasibility and effectiveness of the proposed algorithm have been verified through typical numerical simulations inspired by realistic Martian terrains. Moreover, this attempt using PPF methodology here can be easily reformulated to adjust the powered descent problem with collision avoidance for a flat surface or glide-slope constraint.

Distributed Adaptive and Resilient Control of Multi-Robot Systems With Limited Field of View Interactions

In this letter, we consider two coupled problems for distributed multi-robot systems (MRSs) coordinating with on-board sensors: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rejection of sensor attacks and adaptive tuning of interaction gains</i> . First, MRSs with on-board sensors can be more susceptible to sensor attacks, and therefore must be resilient to such attacks. Second, a typical shortcoming of distributed control frameworks (e.g., potential fields) is that the overall system behavior is highly sensitive to the gain assigned to relative interactions. Therefore, we derive <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> control protocols by employing a static output-feedback technique, guaranteeing bounded <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$L_{2}$</tex-math></inline-formula> gains of the error induced by the attack (fault) signals for a potential-based control framework developed for the particular application of limited fields of view (FOVs) control of MRS with additive sensor and actuator attacks (or faults). Moreover, to overcome the shortcomings of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">general</i> potential-based control framework in the first place, we also apply an adaptive gain tuning scheme based on satisfying <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nominal pairwise interactions</i> , which yields a dynamic balancing of interaction strengths in a robot’s neighborhood. Finally, simulation results using ROS Gazebo are provided to support our theoretical findings.

An Adaptive Finite-Time Force-Sensorless Tracking Control Scheme for Pneumatic Muscle Actuators by an Optimal Force Estimation

The prime challenges of the force control generated by pneumatic muscle actuators (PMAs) have arisen from their highly nonlinear properties, which are perturbed by dynamic uncertainties and external disturbances. To achieve fast response, high accuracy, and robust force tracking performance without using a force sensor, this letter proposes an adaptive finite-time force-sensorless control scheme for a single-joint manipulator configured by a pair of antagonistic PMAs. First, a newly time-varying adaptive optimal force estimation scheme is proposed to obtain the environmental contact force using only position information, such that improvements of transient response and estimated accuracy are assisted by the cost function of the predefined estimation error. Next, the principal control method relied on core elements of a finite-time integral fast terminal sliding mode control procedure is developed. Additionally, a force-based time delay estimation technique is deployed to estimate the lumped uncertainties. Meanwhile, the new adaptive gain law assists in compensating for the remained error of the estimator. The stability and finite-time convergence features of the whole system are demonstrated through Lyapunov theory. Finally, a series of trials are conducted on an actual paradigm with an adjustable environment configuration. The reliability and superiority of our approach are confirmed by comparing the experimental results with other approaches.

Cascaded adaptive integral backstepping sliding mode and super-twisting controller for twin rotor system using bond graph model

This work presents a bond graph (BG) model and a robust cascaded controller for a twin-rotor system (TRS). The BG model accounts for all the energetic and dynamical couplings. An adaptive integral backstepping sliding mode (AIBSM) controller is used in the outer loop to control the slow yaw and pitch dynamics of the mechanical sub-system whereas a higher-order sliding mode (HOSM) observer-based super-twisting algorithm (STA) controller is used in the inner loop to control the fast electromechanical actuator dynamics. The gain of the discontinuous control term of the integral backstepping sliding mode (IBSM) controller is adjusted by using an adaptive switching gain law, where the adaptive gain decreases or increases as the system state variables move closer to or away from a sliding surface; thereby reducing chatter and discontinuities near the sliding manifold, and ensuring a nearly smooth reference signal to the inner-loop controller. The unavailable states are estimated by using an unscented Kalman filter. All the used controllers are shown to be Lyapunov stable. The performance of the developed controller is validated through simulation and experiment, and it is further compared with other existing robust controllers. The proposed controller is robust against un-modeled dynamics and external disturbances, and it performs better, in terms of trajectory tracking error and disturbance rejection, than presently existing controllers for the TRS.

A discrete output feedback 2-SMC using Linear Matrix Inequalities and adaptive switching gain approaches: Real application on a chemical reactor

The chattering phenomenon is one of the most pervasive problems in sliding mode control (SMC), especially for discrete time applications. In this paper, we propose a new discrete output feedback second order sliding mode control (DOF2SMC). The design of this controller is based on the Linear Matrix Inequalities (LMI) approach. Then, an adaptive switching gain (ASG) is incorporated into the discontinuous part of the controller to obtain good closed loop performance in terms of tracking and reducing chattering in the case of systems subject to internal and external disturbances. Simulation results of a steer-by-wire (SBW) system show the effectiveness of the proposed DOF2SMC with ASG. To validate, once again, the performance of the proposed control system, an experimental validation on a transesterification reactor is presented. The obtained results show good closed loop performance.

A novel sliding mode observer-based compound sliding mode current control with active damping for single phase grid-tied inverter system in weak grid

This paper proposes a novel sliding mode observer (SMO)-based compound sliding mode current control (CSMCC) strategy with active damping for the single-phase grid-tied inverter system in weak grid. To decrease the number of measurement sensors and thus reduce system cost, the SMO with rapid response and low chattering level is designed for estimating the inverter-side current and capacitor voltage of LCL-type filter, which is used for feedback control. To enhance robustness against the parameter variation of grid-tied inverter system, the CSMCC is put forward, which is composed of two parts. One part is the equivalent control for grid-tied inverter system with nominal parameters, and the other part is the reaching law-based second-order nonsingular terminal sliding mode control (NTSMC) for compensating the disturbance due to the parameter variations. Since an adaptive gain of switching function is employed and there is integral operation for this discontinuous switching function, the proposed NTSMC strategy not only speed up system response but also attenuate the system chattering level significantly. Moreover, for inhibition of inherent resonance resulting from LCL-type filter, the weighted average current-based active damping is used to provide feedback current for CSMCC. Comprehensive simulation and experimental results show that the proposed strategy can enable the grid-tied inverter system to not only have strong robustness against the filter parameters & grid impedance variations but also improve the quality of grid current, and have satisfactory suppression effect of background grid voltage harmonics on grid current.

Inhibition of androgenic pathway impairs encoding of cerebellar-dependent motor learning in male rats.

Cerebellar-dependent learning is essential for the adaptation of motor and no motor behaviors to changing contexts, and neuroactive steroids-mainly referred to as estrogens-may regulate this process. However, the role of androgens in this process has not been established, although they may affect cerebellar physiology. Thus, this study aims to determine whether the activation of androgenic neural pathways may take part in controlling the vestibuloocular (VOR) and optokinetic reflexes (OKR), which depend on a defined cerebellar circuitry. To answer this question, we acutely blocked the activation of androgen receptors (Ars) using systemic administration of the Ars antagonist flutamide (FLUT; 20mg/Kg) in peripubertal male rats. Then, we evaluated the FLUT effect on general oculomotor performance in the VOR and OKR as well as VOR adaptive gain increases and decreases. We used a paradigm causing fast VOR adaptation that combined in phase/out phase visuo-vestibular stimulations. We found that FLUT impaired the gain increase and decrease in VOR adaptation. However, FLUT altered neither acute nor overtime basal ocular-motor performance in the VOR or OKR. These findings indicate that the activation of androgenic neural pathways participates in phenomena leading to fast VOR adaptation, probably through the modulation of plasticity mechanisms that underlie adaptation of this reflex. Conversely, androgens may not be essential for neural information processing demands in basal ocular-motor reflexes. Moreover, our results suggest that androgens, possibly testosterone and dihydrotestosterone, could rapidly regulate motor memory encoding in the VOR adaptation, acting at both cerebellar and extracerebellar plasticity sites.

Theory of AdaDelSPGD Algorithm in Fiber Laser-Phased Array Multiplex Communication Systems

Stochastic parallel gradient descent (SPGD) algorithm is one of the most promising methods for effective coherent beam combination. However, the algorithm also has some disadvantages, such as slow convergence speed and local extremum. This paper proposes an AdaDelSPGD algorithm, which combines an AdaDelta algorithm with a SPGD algorithm, and improves the traditional AdaDelta algorithm with adaptive gain coefficient. It is worth noting that the adaptive gain coefficient can be adjusted in real time to improve the convergence rate. The effectiveness of the proposed algorithm is verified by relevant simulation experiments, and the results show that the proposed algorithm can significantly improve the convergence speed. Following the experiments with the fiber laser-phased array multiplex communication system, we can draw the conclusion that the addition of communication modulation reduces the beam quality, and the higher the modulation frequency, the worse the beam quality. However, adding the SPGD algorithm can improve the beam quality. The AdaDelSPGD algorithm proposed in this paper can further improve the beam quality, and the bit error rate of communication is also decreased after testing. This provides a foundation for further research on the fiber laser-phased array multiplex communication system.

Homography‐based uncalibrated visual servoing with neural‐network‐assisted robust filtering scheme and adaptive servo gain

AbstractIn this paper, a homography‐based uncalibrated visual servo system with neural‐network‐assisted robust filtering scheme and adaptive servo gain is presented. This system employs a homography‐based task function which is robust to image defects. A neural‐network‐assisted robust filtering method which combines the new form of smooth variable structure filter (SVSF) with a radial basis function (RBF) neural network is proposed to estimate the total Jacobian between task function and robot joints. The RBF neural network in this filtering method plays the role as a corrector to further improve the accuracy and compensate the interference caused by the measurement errors of image features. The controller that directly controls the robot joints based on the estimated total Jacobian is designed for achieving the robustness to robot parameters errors. By adopting this filtering scheme, the visual servo system shows better accuracy and convincing anti‐interference ability. In addition, a novel Q‐learning strategy is introduced for this homography‐based system to make adaptive adjustment for the servo gain. This adaptive gain enables the system to achieve a faster convergence speed while ensuring the accuracy. Several simulations and experiments have been carried out to verify the performance of the proposed system.

Active disturbance rejection control based on inertia estimation and variable gain for servomechanism of industrial robot

This paper proposes an adaptive PID controller based on linear extended state observer (LESO) for the two-degree-of-freedom joint servomechanism of industrial robot with time-varying load, uncertainties of parameters and disturbance. The third-order extended state space equations of the system approximate model is established to obtain LESO which is applied to estimate the state values and the total disturbance. The model reference adaptive algorithm is used to estimate the variable moment of inertia to design the controller parameter for control law which is designed with disturbance compensation. By appropriately selecting the adaptive gain coefficient of model reference adaptive algorithm and the bandwidth of LESO, the influences of parameter uncertainty, unknown dynamics and disturbances are effectively attenuated. Simulation and experimental results show that the proposed method achieves both satisfactory disturbance rejection and tracking performances of the two-degree-of-freedom joint servomechanism.

An adaptive gain based approach for event-triggered state estimation with unknown parameters and sensor nonlinearities over wireless sensor networks

The distributed state and parameter estimation problem is investigated in this paper for discrete-time nonlinear systems subject to sensor nonlinearities and stochastic disturbances over a wireless sensor network. A novel architecture for distributed state estimator is introduced that incorporates adaptive coupling gains to govern the information exchange between the sensor nodes under event-triggering mechanism. The aim of this paper is to provide a scalable structure for unknown parameter identification independent of sensor networks’ complexity. The boundedness of estimation error is ensured in the framework of uniformly ultimately bounded stability by developing an algebraic connectivity based criterion. The estimator gains including proposed coupling gains are then presented as solution to matrix inequalities. Finally, two simulation examples are presented to demonstrate the effectiveness of proposed estimation architecture.

Model-free robust adaptive integral sliding mode impedance control of knee-ankle-toe active transfemoral prosthesis.

Wearing appropriate active prosthesis is the guarantee of daily life for amputees. Normally the controller of the traditional active transfemoral prosthesis is designed based on the mathematical model. The modelling error and the external interference will reduce the control accuracy of the system and make the prosthesis unable to operate in the desired trajectory. Firstly, combined with time delay estimation (TDE), a model-free robust integral sliding mode impedance controller is designed. This method not only suppress the impedance error, but also eliminate the nonlinear relationship and disturbance in the dynamic model. Secondly, an adaptive law is proposed to update the controller gain, which provide stable control effect. Thirdly, the stability of prosthesis closed-loop system is proved by Lyapunov stability theory. Finally, the motor torque is used to drive each joint, and Matlab/Simscape is used to verify the prosthesis control system. From the result of the simulation experiment, the control method has a good tracking effect on each joint. The root mean square error and mean absolute errors of each joint's angle tracking error are 0.6123°, 1.9976°, 0.5574° and 0.2635°, 1.8175°, 0.4796°. Compared with the controller without adaptive gain and impedance control, the control effect is improved, and the plantar pressure of amputees is closer to the sound side. Comparing the results of different controllers, the adaptive integral sliding mode impedance controller with TDE can better track the expected angles of each joint. The gait is more normal. The walking performance of the prosthesis wearers is improved.

Visual–inertial structural acceleration measurement

AbstractStructural vibration measurement is a crucial and necessary step for structural health monitoring. Recently, computer vision‐based techniques have been proposed by researchers to measure structural motion remotely. However, the direct application of vision‐based measurement to practical applications still faces some challenges, mainly because intrinsic camera vibration can introduce significant errors to the measurement results. In this study, a three‐stage approach using an embedded inertial measurement unit is proposed to compensate for the camera movement. First, camera rotations are estimated by employing a complementary filter with an adaptive gain to fuse gyroscope measurement and accelerometer data. Next, binary robust invariant scalable key‐point features are detected from the region of interest and tracked between video frames using a Kanade–Lucas–Tomasi tracker. Finally, structural acceleration is obtained by combining the information for the obtained structural features and the estimated nonstationary camera motion. The performance of the proposed approach is investigated using both a moving handheld camera and a camera mounted on the unmanned aerial vehicle in the laboratory. These results demonstrate that the proposed method can be effectively applied to measure structural vibration, without requiring stationary background features to be available in the video.

Adaptive output feedback control of large-scale nonlinear time-delay systems with uncertain output equations

For a class of large-scale nonlinear time-delay systems with uncertain output equations, the problem of global state asymptotic regulation is addressed by output feedback. The class of systems under consideration are subject to feedforward growth conditions with unknown growth rate and time delays in inputs and outputs. To deal with the system uncertainties and the unknown delays, a novel low-gain observer with adaptive gain is firstly proposed; next, an adaptive output feedback delay-free controller is constructed by combining Lyapunov-Krasovskii functional with backstepping algorithm. Compared with the existing results, the controllers proposed are capable of handling both the uncertain output functions and the unknown time delays in inputs and outputs. With the help of dynamic scaling technique, it is shown that the closed-loop states converge asymptotically to zero, while the adaptive gain is bounded globally. Finally, the effectiveness of our control schemes are illustrated by three examples.

Satellite micro-launcher control: An integrated adaptive-robust and nonlinear approach

In this paper, a composite and multi-technique-based controller for a three-stage micro-launcher is presented. The proposed control law consists in a linear robust component, obtained for the rigid motion using mixed-sensitivity and normalized coprime factor loopshaping, an adaptive command gain, used to compensate the effects of the flexible motion, and a nonlinear component, used for roll control and payload insertion. Moreover, robust stability is ensured in the presence of parametric uncertainty, while also guaranteeing a set of disk margins which accommodate the adaptive gain. Finally, robust performance is validated via structured singular value analysis at successive instants along the trajectory, while the control scheme is tested in simulation upon the micro-launcher’s nonlinear and uncertain dynamics.

Adaptation of Slip Gain for Modified Transient Vector Estimator-Based Speed Control of Induction Machine Drive

Modified transient vector estimator (MTVE) based speed control scheme that combines the high transient-performance features of rotor field oriented control with the robustness features of scalar control is presented in literature. However, MTVE scheme involves the calculation of slip gain to obtain torque reference. Either inaccurate estimation or variation in the estimated slip gain can result in the degradation of performance of MTVE control. In order to overcome this problem, this paper proposes a slip gain adaptation scheme, that is independent of speed of operation. The proposed method uses d-axis component of stator voltage to obtain expression for disorientation factor and works by matching all the control side variables with that of actual machine variables, and uses a simple PI controller to implement slip gain adaptation. The impact of inaccurate slip gain estimate on the dq-components of various currents, voltages, feed-forward components, and hence on the torque and flux of the machine are analyzed in this paper. The proposed adaptation scheme is suitable for wide speed range operation, in contrast to the existing slip gain adaptation methods, where open loop gain is dependent on the synchronous frequency information. The proposed adaptation scheme is validated using detailed simulation and experimental results. Comparison of the proposed adaptation method with the existing methods is also presented in this paper.

Design and Performance Analysis of NadamSPGD Algorithm for Sensor-Less Adaptive Optics in Coherent FSOC Systems

Sensor-less adaptive optics (SLAO) based on stochastic parallel gradient descent (SPGD) is effective for the compensation of atmospheric turbulence in coherent free-space optical communication (CFSOC) systems. However, SPGD converges slowly and easily falls into local extremes. Therefore, we propose a novel NadamSPGD algorithm for efficient wavefront correction that combines Nesterov-accelerated adaptive moment estimation (Nadam) and SPGD. Specifically, Nesterov’s accelerated gradient momentum (NAG) and adaptive gain coefficients are integrated to conventional SPGD to accelerate its convergence speed and avoid converging to extremum points. Theoretical analysis, numerical simulations and experimental results demonstrate that NadamSPGD can increase the convergence speed by ~50% and significantly improve the robustness of parameters, and thus more efficiently suppress the negative effects of atmospheric turbulence on mixing efficiency (ME) and bit error rate (BER). Our algorithm also presents better dynamic performance under strong turbulence and high Greenwood frequency conditions, and it is more suitable for real-time SLAO systems. This study proves that the NadamSPGD algorithm is suitable for SLAO in the CFSOC system and is a viable substitute for SPGD to improve the quality of optical communications.

Barrier Function Adaptive Nonsingular Terminal Sliding Mode Control Approach for Quad-Rotor Unmanned Aerial Vehicles.

This paper proposes a barrier function adaptive non-singular terminal sliding mode controller for a six-degrees-of-freedom (6DoF) quad-rotor in the existence of matched disturbances. For this reason, a linear sliding surface according to the tracking error dynamics is proposed for the convergence of tracking errors to origin. Afterward, a novel non-singular terminal sliding surface is suggested to guarantee the finite-time reachability of the linear sliding surface to origin. Moreover, for the rejection of the matched disturbances that enter into the quad-rotor system, an adaptive control law based on barrier function is recommended to approximate the matched disturbances at any moment. The barrier function-based control technique has two valuable properties. First, this function forces the error dynamics to converge on a region near the origin in a finite time. Secondly, it can remove the increase in the adaptive gain because of the matched disturbances. Lastly, simulation results are given to demonstrate the validation of this technique.